Challenges aired at Health Data Initiative Forum

A major bash by the Department of Health and Human Services and the Institute of Medicine–together with the NIH, EPA, and others–drew hundreds of people yesterday in Washington, DC to discuss the use of government data in health care. By placing “challenges” in the title to this article, I’m indulging in a play on words. Most readers will come expecting me to talk about problems that require grappling and resolution. But the “challenges” I’m talking about are contests held by numerous institutions to produce applications that consume health care data and that generate benefits for patients, doctors, policy makers, and the public at large.

The challenges to which so many developers have responded draw on data that HHS has loaded in a programmable format onto Health.Data.Gov–and that they continue to release at a fast clip (see for instance the Health Indicators Warehouse). The zeal with with HHS has organized its data under convenient APIs puts it among the foremost of agencies in the open government movement.

Todd Park, HHS CTO and hero to everything in the open government movement, described the “datapalooza” as follows: “Today is just a day of massive celebration.” And there was certainly a lot of mutual back-slapping among Obama Administration leaders on the stage. But the strength of the new applications shown off at the conference proved there was indeed reason to celebrate. The release of data and its use by developers ranging from college kids to international corporations is a non-partisan cause for exultation.

Kathleen Sebelius, secretary of HHS, during opening session

By bringing us to a new plateau, these apps also show some of the next steps we need to take in health care to extract real improvements in care and costs savings from the data on which the apps are based. So there are actually “challenges” of the problematic type implicit in the conference after all. I’ll start by describing the progress shown by some of the apps I saw; a briefer but more comprehensive list can be found on the blog of my colleague, Brian Ahier. Then I’ll move on to next steps.

A sample of recent health-care apps and challenges

In the interest of full disclosure, I should mention that I submitted some ratings of apps as a judge in the Health 2.0 Developer Challenge. Some of the interesting projects I discovered at the conference include:

SleepBot

This won the top prize in a special contest run by the Institute of Medicine and the National Academy of Engineering for college students, Go Viral to Improve Health. The app was developed by two students, one of whom said she never gets enough sleep because she goes to school full-time and works two jobs. How, one might ask, did she have time to write a winning app? I hope that after winning this prize she can quit one job.

The app makes it extremely easy to measure sleep and compare different nights. You just press a button that says “I’m going to sleep!” and the app records the current time. If you press your button in the morning to turn off your alarm on the mobile device, the app records you as waking up. You can display your sleep times for multiple nights and save the data for running statistics. I think this app would make an excellent complement for the Zeo sleep monitor, which I’ve covered in other blogs.

This site connects doctors and patients, somewhat like HealthTap, which I covered two months ago. The data aspect of Organized Wisdom that I find interesting is their display of common ailments–all the usuals you’d expect, such as asthma and diabetes–associated with each geographic area you search for. This data comes straight from healthdata.gov. You can also click on each ailment to pull up an NIH page about it. This data could be used by doctors to intervene more effectively in the locations they work in, or by patients to choose where to live or prepare for the risks where they do live.

I should note that the conference also highlighted a journalist’s site called Ozioma that provides localized health data in a form that makes it easy to develop stories and plug in useful facts.

This patient portal, run by the New York-Presbyterian hospital, illustrates the evolution of current clinical institutions toward patient-centered care, such a focus of health activists. By exposing patient data on a portal, a hospital can turn its EHR (electronic health record) to a PHR (personal health record). MyNYP also resembles many hospitals in exposing their data in the lithe CCR format and providing an interface to Microsoft HealthVault, so that patients can mingle their hospital data with other data they accumulate. A web developer from MyNYP told me they provide a limited way for a patient also to upload data. I expect this feature will expand as patients demand ways to provide their doctors with observations of daily living.

The interface to MyNYP is clean and readable, but one aspect shows the complexity of demands for usable interfaces. Each hospital visit is a separate item, providing its own button for you to upload its data to HealthVault. For the neediest patients–those likely to care most about their data–this could mean having to click buttons dozens of times to upload a few months’ worth of data. A simple list of checkboxes on the side and an “All” button, such as Gmail provides, could let patients select data more easily.

This is heavy-duty software for helping hospitals and clinics meet the requirements of “accountable delivery,” which could be the formation of an Accountable Care Organization (one of the hot trends in current movements to lower health care costs) or some other type of integrated care. For instance, it can help you check areas of variability (are one set of doctors treating a condition substantially differently from another set?). The software helps organizations integrate clinical, pharmacy, and other data. It is designed to let organizations keep their current EHRs and run the accountability functions on top of them.

I held a special regard for this project because the presentation went very fast and raced through a number of buzzwords. I trust that experts in the field appreciated the importance of the goals and design, but the general public could easily have bypassed the project.

If you can figure out from the name what this project does, you don’t need to read this blog. The project accumulates data about outbreaks of food-related illness and data that traces the origin of food delivered to various stores and restaurants. It provides elegant and animated visualizations that help an epidemiologist quickly track down the origin of food poisoning, hopefully in time to prevent further victims.

As with Lumeris Maestro, the presentation of this project at the conference was rather pro forma. The presenters didn’t even bother to update their prepared script to mention the recent spectacular and widely reported outbreak of E coli deaths in Europe. But the demo persuasively conveyed the value of this software under crisis conditions.

This site also excited a special sympathy in me because it’s heavily based on taxonomies. When searching for in-depth data about a heart attack, it’s important to know that clinicians refer to it as a myocardial infarction. Healthline correlates all these different forms of terminology (along with diagnostic codes) and offers rich information to the general public, including beautiful anatomical diagrams.

From the app to the ecosystem

The notion of an “ecosystem” for health care apps was invoked at least twice during yesterday’s conference, by Park and by Risa Lavizzo-Mourey, President of the Robert Wood Johnson Foundation. I believe they were conceiving this ecosystem as a business environment that made software development lucrative enough to attract more apps. Kathleen Sebelius, HHS secretary, indicated in her opening remarks that the contestents for this year’s challenges had to demonstrate sustainable business models as well as good applications. And an initiative called StartUpHealth was announced by Organized Wisdom, planning to provide funding and mentoring over a series of years to promising health-related enterpreneurs. All well and good. But I will use “ecosystem” in this section to denote a rather different set of supports and usage.

The first part of the ecosystem is getting accurate and useful data for the apps to play with. Opening government databases is critically important, but improving them is the next step. Much of the practice required by the government under “meaningful use” criteria is directed at making the data submitted by doctors is complete, consistent, and truly reflective of what they do in the clinic. Just one common example of dirty data is provided by diagnostic codes, which researchers complain are usually chosen for billing for the highest possible payment rather than indicating what’s really wrong with the patient.

App developers should also coordinate with each other to use data formats in common. Letting a thousand flowers bloom should entail letting a thousand XML schemas proliferate. As we’ve seen in this article, healthdata.gov itself offers some degree of standardization, and so do industry formats such as the CCR.

More standards will need to be introduced so that consumers can easily plug machines such as blood pressure monitors into commodity cell phones, and let the apps recognize and communicate with such external devices.

Once the app is outfitted and running, we need to incorporate its results into actual changes in patient care. This reflects a question I asked of several app developers: your tool will be eagerly adopted by patients who are responsible, tech savvy, and conscious of their health options. But those are the patients already most likely to take care of their health. What about the famously unresponsive patient? (This population was highlighted at the conference by a project called ElizaLIVE.) A useful app will be able to integrate with an EHR or PHR, along with devices consulted by the patient and any other interventions planned by the doctor or by public health officials.

Thus, the ecosystem I envision looks like this figure:

So the health care field is left with plenty of challenge, after all, to handle its challenges. A lot is going on in this area. The National Cancer Institute, Walgreens, and Sanofi-aventis all announced new challenges. The University of Michigan announced a graduate program in health informatics, and the Robert Wood Johnson Foundation announced a Health Data Consortium (of which O’Reilly Media is a member) for pushing the incorporation of data into more apps and into health initiatives in general.

Break-out session

The crowd dwindled during the conference, till at the final session–where federal CTO Aneesh Chopra and my own CEO, Tim O’Reilly, spoke–only a third of the original attendees remained. But the break-out sessions I saw, where the real work of the conference took place, were well attended. These sessions covered topics such as recently released data sets, mapping, preserving privacy, and accountable care. The feeling left at the end of the day was that a lot is going on.

Get the O’Reilly Data Newsletter

It’s so nice to see observations of daily living (ODLs) becoming part of everyday conversations about health and health care. We at Project HealthDesign, a national program of the Robert Wood Johnson Foundation, are excited to see all of the developer challenges and product innovations that are beginning to appear in the health application marketplace. But we’re even more enthused to see so many app developers taking the baton by allowing individuals to track their own health data and ODLs. We look forward to hearing about more provider groups that take this approach, much like New York Presbyterian did as they developed MyNYP.

I recently wrote a blog post that describes my view of the health information ecosystem (http://bit.ly/luVxG8), which includes data arising from both clinical health care and health in everyday living (like ODLs). Additionally, I’m encouraged to see so many people extending this idea by recognizing the need for a broader health ecosystem that includes clean and accurate health data; innovation in health applications and related devices; good data practices in clinical settings; and data-informed clinical decision-making that brings clinicians and patients together as partners in health. Thanks for pointing out some of the new landmarks in the ecosystem!